Sanghyun Hong

  • Oregon State University, Corvallis, OR, USA
  • University of Maryland, College Park, MD, USA (PhD 2021)

According to our database1, Sanghyun Hong authored at least 26 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


Online presence:



A Scanner Deeply: Predicting Gaze Heatmaps on Visualizations Using Crowdsourced Eye Movement Data.
IEEE Trans. Vis. Comput. Graph., 2023

Publishing Efficient On-device Models Increases Adversarial Vulnerability.
CoRR, 2022

Time Series Forecasting with Hypernetworks Generating Parameters in Advance.
CoRR, 2022

Mining Causality from Continuous-time Dynamics Models: An Application to Tsunami Forecasting.
CoRR, 2022

AdamNODEs: When Neural ODE Meets Adaptive Moment Estimation.
CoRR, 2022

Improving cross-platform binary analysis using representation learning via graph alignment.
Proceedings of the ISSTA '22: 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, South Korea, July 18, 2022

Data Poisoning Won't Save You From Facial Recognition.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

Building Secure and Reliable Deep Learning Systems from a Systems Security Perspective.
PhD thesis, 2021

Handcrafted Backdoors in Deep Neural Networks.
CoRR, 2021

Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference.
Proceedings of the 9th International Conference on Learning Representations, 2021

Certified Malware in South Korea: A Localized Study of Breaches of Trust in Code-Signing PKI Ecosystem.
Proceedings of the Information and Communications Security - 23rd International Conference, 2021

On the Effectiveness of Regularization Against Membership Inference Attacks.
CoRR, 2020

On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping.
CoRR, 2020

How to 0wn the NAS in Your Spare Time.
Proceedings of the 8th International Conference on Learning Representations, 2020

Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset.
CoRR, 2019

Terminal Brain Damage: Exposing the Graceless Degradation in Deep Neural Networks Under Hardware Fault Attacks.
Proceedings of the 28th USENIX Security Symposium, 2019

Shallow-Deep Networks: Understanding and Mitigating Network Overthinking.
Proceedings of the 36th International Conference on Machine Learning, 2019

Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks.
CoRR, 2018

Peek-a-boo: Inferring program behaviors in a virtualized infrastructure without introspection.
Comput. Secur., 2018

On Integrating Knowledge Graph Embedding into SPARQL Query Processing.
Proceedings of the 2018 IEEE International Conference on Web Services, 2018

Go Serverless: Securing Cloud via Serverless Design Patterns.
Proceedings of the 10th USENIX Workshop on Hot Topics in Cloud Computing, 2018

PAGE: Answering Graph Pattern Queries via Knowledge Graph Embedding.
Proceedings of the Big Data - BigData 2018, 2018

Summoning Demons: The Pursuit of Exploitable Bugs in Machine Learning.
CoRR, 2017

SENA: Preserving Social Structure for Network Embedding.
Proceedings of the 28th ACM Conference on Hypertext and Social Media, 2017